Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
eval = identical(tolower(Sys.getenv("NOT_CRAN")), "true"),
out.width = "100%"
)
use_suggested_pkgs <- c((requireNamespace("dplyr")),
(requireNamespace("scales")),
(requireNamespace("ggplot2")),
(requireNamespace("censobr")))
use_suggested_pkgs <- all(use_suggested_pkgs)
## ----eval=FALSE, message=FALSE, warning=FALSE---------------------------------
# # From CRAN
# install.packages("geobr")
#
# # Development version
# utils::remove.packages('geobr')
# devtools::install_github("ipeaGIT/geobr", subdir = "r-package")
#
## ----eval=use_suggested_pkgs, message=FALSE, warning=FALSE, results='hide'----
library(geobr)
library(ggplot2)
library(sf)
library(dplyr)
## ----eval=use_suggested_pkgs, message=FALSE, warning=FALSE--------------------
# Available data sets
datasets <- list_geobr()
head(datasets)
## ----eval=use_suggested_pkgs, message=FALSE, warning=FALSE--------------------
# State of Sergige
state <- read_state(
code_state="SE",
year=2018,
showProgress = FALSE
)
# Municipality of Sao Paulo
muni <- read_municipality(
code_muni = 3550308,
year=2010,
showProgress = FALSE
)
ggplot() +
geom_sf(data = muni, color=NA, fill = '#1ba185') +
theme_void()
## ----eval=TRUE, message=FALSE, warning=FALSE, results='hide'------------------
# All municipalities in the state of Minas Gerais
muni <- read_municipality(code_muni = "MG",
year = 2007,
showProgress = FALSE)
# All census tracts in the state of Rio de Janeiro
cntr <- read_census_tract(
code_tract = "RJ",
year = 2010,
showProgress = FALSE
)
head(muni)
## ----eval=TRUE, message=FALSE, warning=FALSE----------------------------------
# read all intermediate regions
inter <- read_intermediate_region(
year = 2017,
showProgress = FALSE
)
# read all states
states <- read_state(
year = 2019,
showProgress = FALSE
)
head(states)
## ----eval=use_suggested_pkgs, message=FALSE, warning=FALSE, fig.height = 8, fig.width = 8, fig.align = "center"----
# Remove plot axis
no_axis <- theme(axis.title=element_blank(),
axis.text=element_blank(),
axis.ticks=element_blank())
# Plot all Brazilian states
ggplot() +
geom_sf(data=states, fill="#2D3E50", color="#FEBF57", size=.15, show.legend = FALSE) +
labs(subtitle="States", size=8) +
theme_minimal() +
no_axis
## ----eval=use_suggested_pkgs, message=FALSE, warning=FALSE, fig.height = 8, fig.width = 8, fig.align = "center"----
# Download all municipalities of Rio
all_muni <- read_municipality(
code_muni = "RJ",
year= 2010,
showProgress = FALSE
)
# plot
ggplot() +
geom_sf(data=all_muni, fill="#2D3E50", color="#FEBF57", size=.15, show.legend = FALSE) +
labs(subtitle="Municipalities of Rio de Janeiro, 2000", size=8) +
theme_minimal() +
no_axis
## ----eval=use_suggested_pkgs, message=FALSE, warning=FALSE, results='hide'----
# Read data.frame with life expectancy data
df <- utils::read.csv(system.file("extdata/br_states_lifexpect2017.csv", package = "geobr"), encoding = "UTF-8")
states$name_state <- tolower(states$name_state)
df$uf <- tolower(df$uf)
# join the databases
states <- dplyr::left_join(states, df, by = c("name_state" = "uf"))
## ----eval=use_suggested_pkgs, message=FALSE, warning=FALSE, fig.height = 8, fig.width = 8, fig.align = "center"----
ggplot() +
geom_sf(data=states, aes(fill=ESPVIDA2017), color= NA, size=.15) +
labs(subtitle="Life Expectancy at birth, Brazilian States, 2014", size=8) +
scale_fill_distiller(palette = "Blues", name="Life Expectancy", limits = c(65,80)) +
theme_minimal() +
no_axis
## ----eval = use_suggested_pkgs------------------------------------------------
library(censobr)
hs <- read_households(year = 2010,
showProgress = FALSE)
## ----eval = use_suggested_pkgs, warning = FALSE-------------------------------
esg <- hs |>
collect() |>
group_by(code_muni) |> # (a)
summarize(rede = sum(V0010[which(V0207=='1')]), # (b)
total = sum(V0010)) |> # (b)
mutate(cobertura = rede / total) |> # (c)
collect() # (d)
head(esg)
## ----eval = use_suggested_pkgs, warning = FALSE-------------------------------
# download municipality geometries
muni_sf <- geobr::read_municipality(year = 2010,
showProgress = FALSE)
# merge data
muni_sf$code_muni <- as.character(muni_sf$code_muni)
esg_sf <- left_join(muni_sf, esg, by = 'code_muni')
# plot map
ggplot() +
geom_sf(data = esg_sf, aes(fill = cobertura), color=NA) +
labs(title = "Share of households connected to a sewage network") +
scale_fill_distiller(palette = "Greens", direction = 1,
name='Share of\nhouseholds',
labels = scales::percent) +
theme_void()
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.